




'''simple docstring'''


from multiprocessing import Lock, Pipe, Process

# lock used to ensure that two processes do not access a pipe at the same time
UpperCAmelCase_					=   Lock()


def     SCREAMING_SNAKE_CASE							(   a_						:				str					,       a_						:				Tuple					,       a_						:				Dict					,       a_						:				Optional[Any]					,       a_						:				str					,       a_						:				Any					,       a_						:				Optional[Any]      ):
  global process_lock

  # we perform n swaps since after n swaps we know we are sorted
  # we *could* stop early if we are sorted already, but it takes as long to
  # find out we are sorted as it does to sort the list with this algorithm
  for i in range(0					,       10      ):
    if (i + position) % 2 == 0 and r_send is not None:
      # send your value to your right neighbor
      process_lock.acquire()
      r_send[1].send(a_      )
      process_lock.release()

      # receive your right neighbor's value
      process_lock.acquire()
      __a								=       rr_cv[0].recv()
      process_lock.release()

      # take the lower value since you are on the left
      __a								=       min(a_					,       a_      )
    elif (i + position) % 2 != 0 and l_send is not None:
      # send your value to your left neighbor
      process_lock.acquire()
      l_send[1].send(a_      )
      process_lock.release()

      # receive your left neighbor's value
      process_lock.acquire()
      __a								=       lr_cv[0].recv()
      process_lock.release()

      # take the higher value since you are on the right
      __a								=       max(a_					,       a_      )
    # after all swaps are performed, send the values back to main
  result_pipe[1].send(a_      )


def     SCREAMING_SNAKE_CASE							(   a_						:				List[str]      ):
  __a								=       []
  __a								=       []
  # initialize the list of pipes where the values will be retrieved
  for _ in arr:
    result_pipe.append(Pipe()      )
  # creates the processes
  # the first and last process only have one neighbor so they are made outside
  # of the loop
  __a								=       Pipe()
  __a								=       Pipe()
  process_array_.append(
      Process(
          target=a_					,       args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0])					,       )      )
  __a								=       temp_rs
  __a								=       temp_rr

  for i in range(1					,       len(a_      ) - 1      ):
    __a								=       Pipe()
    __a								=       Pipe()
    process_array_.append(
        Process(
            target=a_					,       args=(i, arr[i], temp_ls, temp_rs, temp_lr, temp_rr, result_pipe[i])					,       )      )
    __a								=       temp_rs
    __a								=       temp_rr

  process_array_.append(
      Process(
          target=a_					,       args=(
              len(a_      ) - 1,
              arr[len(a_      ) - 1],
              temp_ls,
              None,
              temp_lr,
              None,
              result_pipe[len(a_      ) - 1],
          )					,       )      )

  # start the processes
  for p in process_array_:
    p.start()

  # wait for the processes to end and write their values to the list
  for p in range(0					,       len(a_      )      ):
    __a								=       result_pipe[p][0].recv()
    process_array_[p].join()
  return arr


def     SCREAMING_SNAKE_CASE							(   ):
  __a								=       list(range(10					,       0					,       -1      )      )
  print('Initial List'      )
  print(*a_      )
  __a								=       odd_even_transposition(a_      )
  print('Sorted List\n'      )
  print(*a_      )


if __name__ == "__main__":
  main()









'''simple docstring'''


import warnings
from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase_					=   logging.get_logger(__name__)

UpperCAmelCase_					=   {
    "nvidia/segformer-b0-finetuned-ade-512-512": (
        "https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json"
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}





class  __lowercase    (	__magic_name__			):
   _a    						=   """segformer"""







   def __init__(						self   ,				UpperCamelCase=3   ,				UpperCamelCase=4   ,				UpperCamelCase=[2, 2, 2, 2]   ,				UpperCamelCase=[8, 4, 2, 1]   ,				UpperCamelCase=[32, 64, 160, 256]   ,				UpperCamelCase=[7, 3, 3, 3]   ,				UpperCamelCase=[4, 2, 2, 2]   ,				UpperCamelCase=[1, 2, 5, 8]   ,				UpperCamelCase=[4, 4, 4, 4]   ,				UpperCamelCase="gelu"   ,				UpperCamelCase=0.0   ,				UpperCamelCase=0.0   ,				UpperCamelCase=0.1   ,				UpperCamelCase=0.02   ,				UpperCamelCase=0.1   ,				UpperCamelCase=1e-6   ,				UpperCamelCase=256   ,				UpperCamelCase=255   ,				**UpperCamelCase   ,				)					->     int:
     super().__init__(**UpperCamelCase   )

     if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
       warnings.warn(
           'Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be'
           ' removed, as the behaviour will default to that of reshape_last_stage = True.'   ,				UpperCamelCase   ,				)

     __a								=       num_channels
     __a								=       num_encoder_blocks
     __a								=       depths
     __a								=       sr_ratios
     __a								=       hidden_sizes
     __a								=       patch_sizes
     __a								=       strides
     __a								=       mlp_ratios
     __a								=       num_attention_heads
     __a								=       hidden_act
     __a								=       hidden_dropout_prob
     __a								=       attention_probs_dropout_prob
     __a								=       classifier_dropout_prob
     __a								=       initializer_range
     __a								=       drop_path_rate
     __a								=       layer_norm_eps
     __a								=       decoder_hidden_size
     __a								=       kwargs.get('reshape_last_stage'   ,				UpperCamelCase   )
     __a								=       semantic_loss_ignore_index





class  __lowercase    (	__magic_name__			):
   _a    						=   version.parse("""1.11"""			)







   @property
   def 		UpperCamelCase__      (						self   )					->     Mapping[str, Mapping[int, str]]:
     return OrderedDict(
         [
             ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
         ]   )







   @property
   def 		UpperCamelCase__      (						self   )					->     float:
     return 1e-4







   @property
   def 		UpperCamelCase__      (						self   )					->     int:
     return 12



